gov.noaa.idp:Global Precipitation Analysis via CMORPHeng; USAutf8datasetNOAA IDP GIS Support TeamDOC/NOAA/NWS/NCEP/IDP-GIS > National Oceanic & Atmospheric Administration > IDP-GISPosition Type9 999-999-9999CityState99999USAidp.gis.support@noaa.govMonday-Friday, 8am-4pm Eastern TimepointOfContact2016-05-19T15:40:04+00:00ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded DataISO 19115-2:2009(E)CMORPH AnalysisGlobal precipitation analysis2016-01-01revisionCMORPH (CPC MORPHing technique) produces global precipitation analyses at very high spatial and temporal resolution.
This technique uses precipitation estimates that have been derived from low orbiter satellite microwave observations exclusively, and whose features are transported via spatial propagation
information that is obtained entirely from geostationary satellite IR data. At present we incorporate precipitation estimates derived from the passive microwaves aboard the DMSP 13, 14 and 15
(SSM/I), the NOAA-15, 16, 17 and 18 (AMSU-B), and AMSR-E and TMI aboard NASA's Aqua and TRMM spacecraft, respectively. These estimates are generated by algorithms of Ferraro (1997) for SSM/I,
Ferraro et al. (2000) for AMSU-B and Kummerow et al. (2001) for TMI. Note that this technique is not a precipitation estimation algorithm but a means by which estimates from existing microwave
rainfall algorithms can be combined. Therefore, this method is extremely flexible such that any precipitation estimates from any microwave satellite source can be incorporated. With regard
to spatial resolution, although the preciptation estimates are available on a grid with a spacing of 8 km (at the equator), the resolution of the individual satellite-derived estimates is
coarser than that - more on the order of 12 x 15 km or so. The finer "resolution" is obtained via interpolation. In effect, IR data are used as a means to transport the microwave-derived
precipitation features during periods when microwave data are not available at a location. Propagation vector matrices are produced by computing spatial lag correlations on successive images
of geostationary satellite IR which are then used to propagate the microwave derived precipitation estimates. This process governs the movement of the precipitation features only. At a
given location, the shape and intensity of the precipitation features in the intervening half hour periods between microwave scans are determined by performing a time-weighting interpolation
between microwave-derived features that have been propagated forward in time from the previous microwave observation and those that have been propagated backward in time from the following
microwave scan. We refer to this latter step as "morphing" of the features.How the data should be usedongoingPingping Xie;Robert JoyceDOC/NOAA/NWS/Climate Prediction Center > National Oceanic & Atmospheric Administrationposition here9 999-999-9999CityST99999USAPingping.Xie@noaa.gov;Robert.Joyce@noaa.govFix next business day, Monday-Friday, 8am-4pm Eastern Timecustodianatmosphere,united states of america,monitoring,precipitation,meteorological hazards,global precipitation,microwave satellite,infrared,geostationary satellite,climatology,meteorology,natural hazards,environmental impacts,
drought,precipitation,atmospheric phenomena,water management,precipitation anomalythemeGeographic keywordsplaceeng;USAclimatologyMeteorologyAtmospheremodeled period9999-99-999999-99-99Additional information goes here|||||CMORPH Analysis9999publicationPingping Xie;Robert JoyceDOC/NOAA/NWS/Climate Prediction Center > National Oceanic & Atmospheric AdministrationPingping.Xie@noaa.gov;Robert.Joyce@noaa.govMonday-Friday, 8am-4pm Eastern TimecustodianCMORPH (CPC MORPHing technique) produces global precipitation analyses at very high spatial and temporal resolution.
This technique uses precipitation estimates that have been derived from low orbiter satellite microwave observations exclusively, and whose features are transported via spatial propagation
information that is obtained entirely from geostationary satellite IR data. At present we incorporate precipitation estimates derived from the passive microwaves aboard the DMSP 13, 14 and 15
(SSM/I), the NOAA-15, 16, 17 and 18 (AMSU-B), and AMSR-E and TMI aboard NASA's Aqua and TRMM spacecraft, respectively. These estimates are generated by algorithms of Ferraro (1997) for SSM/I,
Ferraro et al. (2000) for AMSU-B and Kummerow et al. (2001) for TMI. Note that this technique is not a precipitation estimation algorithm but a means by which estimates from existing microwave
rainfall algorithms can be combined. Therefore, this method is extremely flexible such that any precipitation estimates from any microwave satellite source can be incorporated. With regard
to spatial resolution, although the preciptation estimates are available on a grid with a spacing of 8 km (at the equator), the resolution of the individual satellite-derived estimates is
coarser than that - more on the order of 12 x 15 km or so. The finer "resolution" is obtained via interpolation. In effect, IR data are used as a means to transport the microwave-derived
precipitation features during periods when microwave data are not available at a location. Propagation vector matrices are produced by computing spatial lag correlations on successive images
of geostationary satellite IR which are then used to propagate the microwave derived precipitation estimates. This process governs the movement of the precipitation features only. At a
given location, the shape and intensity of the precipitation features in the intervening half hour periods between microwave scans are determined by performing a time-weighting interpolation
between microwave-derived features that have been propagated forward in time from the previous microwave observation and those that have been propagated backward in time from the following
microwave scan. We refer to this latter step as "morphing" of the features.DATA ANALYSIS AND VISUALIZATION > GEOGRAPHIC INFORMATION SYSTEMS > WEB-BASED GEOGRAPHIC INFORMATION SYSTEMSDATA MANAGEMENT/DATA HANDLING > DATA SEARCH AND RETRIEVALDATA ANALYSIS AND VISUALIZATION > VISUALIZATION/IMAGE PROCESSINGthemeNoneNoneArcGIS Map Service10.2.21-180180-6060tightWeb Page for the serviceN/AhttpWeb BrowserLocation for the resource page of the serviceinformationArcGIS for Server REST endpoint for cached map servicePlace to put the URL of the Rest endpoint for the servicehttpArcGIS Map ServiceName of cached map serviceGeneral description of ServiceinformationDynamic Map Servicehttps://idpgis.ncep.noaa.gov/arcgis/rest/services/NWS_Climate_Outlooks/cpc_cmorph_dly_025deg/MapServerhttpArcGIS Map ServiceGlobal Precipitation Analysis via CMORPHEstimates of precipitation based on satellite measurements of clouds and temperatureinformationWMS Get CapabilitieshttpOpen Geospatial Consortium Web Map Service (WMS)cpc_cmorph_dly_025deg Capabilities document for Open Geospatial Consortium compliant Web Map ServiceinformationWFS Get CapabilitiesURL for capabilities documenthttpOpen Geospatial Consortium Web Feature Service (WFS)Name of WFS documentCapabilities document for Open Geospatial Consortium compliant Web Feature ServiceinformationNOAA IDP GIS Support TeamDOC/NOAA/NWS/NCEP/IDP-GIS > National Oceanic & Atmospheric Administration > IDP-GIS9 999-999-9999city nameState99999USAidp.gis.support@noaa.govhttp://ftp.cpc.ncep.noaa.gov/GIS/GRADS_GIS/GeoTIFF/CMORPH_DLY/httpDownloaddistributorzip file; geo-tiffs9999http://ftp.cpc.ncep.noaa.gov/GIS/GRADS_GIS/GeoTIFF/CMORPH_DLY/httpThis ISO metadata record was created using the 'Check and Save to File' (with form validation) function of the GRIIDC ISO 19115-2 Metadata Editor on 2016-05-17T21:49:46+00:00